It is very important to forecast electricity price in a deregulated electricity market for choosing
the bidding strategy, and it is the most important signal for other players. It engulfs
information for both customers and producers in order to maximize their profit. Thus, choosing
the best method of price forecasting is a crucial task to have the most accurate forecast. In this
paper the price forecasting is done based on different methods including autoregressive
integrated moving average (ARIMA), artificial neural network (ANN) and fuzzy regression. The
method is examined by using data of Ontario electricity market. The results of different
methods are compared and the best method is chosen. Fuzzy regression model is a new
method in forecasting and it is rare in the literature review; it is showed that it leads to the best
results.
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